The Role of Generative AI in Democratizing E-Commerce via ONDC

The Open Network for Digital Commerce aims to let any buyer app connect with any seller app, much as UPI did for payments. Generative AI could make it far easier for small shops to take part. This article explains how ONDC is structured, where generative tools help, and what sellers should keep in mind.

A Quick Look at ONDC

On most marketplaces, the buyer, the seller, and the logistics provider all operate inside one company’s platform. ONDC separates these roles. A shopper can use one app, a kirana store can list products through a different seller app, and delivery can be handled by yet another provider, all communicating through common protocols.

This openness lowers the dependence on any single platform. The catch is that small businesses still need to create digital catalogues, set prices, and respond to customers, which can be daunting for owners with limited time or technical skills.

How Generative AI Lowers the Barriers

Generative AI models produce text, images, and speech from simple prompts. For a neighbourhood shopkeeper, that can turn hours of catalogue work into minutes. Some seller apps on the network have begun offering such features, though capabilities vary widely.

Common use cases include:

• Catalogue creation: photographing a product and letting a model suggest a title, description, and category.
• Language support: writing listings in a regional language and automatically producing versions in others.
• Voice onboarding: letting sellers describe their inventory by speaking rather than typing.
• Customer replies: drafting answers to common questions about sizes, delivery, or returns.
• Image cleanup: removing cluttered backgrounds from phone photos so products look presentable.

On the buyer side, conversational search could let someone ask for “a cotton saree under a modest budget for a wedding” in their own words, with the system translating that into structured queries across many sellers.

Limits and Responsibilities

Generative models sometimes invent details, a problem often called hallucination. A description might claim a fabric is organic or a gadget is waterproof when it is not. Sellers remain responsible for what they list, so every AI-generated description should be checked against the actual product before publishing.

There are also fairness questions. If AI tools are offered only by a few well-funded seller apps, the advantage could concentrate rather than spread. Open models and shared language resources help keep the playing field level.

Data handling matters too. Sellers should understand what information their chosen app collects and whether product images or customer chats are used to train models.

What It Adds Up To

ONDC opens the door to digital commerce, and generative AI can help small sellers walk through it by simplifying cataloguing, translation, and customer service. The benefits are real but depend on careful review of AI output and broad access to these tools across the network.